Companies employ business process management suites (BPMS) to model, document, automate, govern and monitor complex repetitive processes. A process' surrounding conditions and contextual constraints tend to change frequently and rapidly. The changes may include all sorts of suddenly occurring exceptional situations such as short-term changes in legislative regulations and administrative guidelines that are to be obeyed, unexpected resource unavailability which must be compensated for, additional customer requests that should be addressed, suddenly occurring workload peaks that require simplifying processes to successfully handle the workload, and the like. Business process end users face the need to flexibly read on the exceptional situations at low costs while still adhering to the “business goals,” such as deliverables or interfaces, of the end-to-end processes they participate in. Companies set themselves apart from their competitive environment by both being able to dynamically adapt to exceptional situations while still taking advantage of the inherent benefits of a BPMS infrastructure (such as monitoring process measures and tracking progress, enforcing mandatory process steps and constraining resource consumption, etc.). Accordingly, process flexibility helps companies broaden the spectrum of BPMS use-cases and, thus, to dramatically improve their “return of investment” on BPMS acquisitions.
Having the means to flexibly adapt processes to exceptional situations opens up a new range of highly dynamic business scenarios to be supported through BPMS technology. In many cases, manually reengineering the underlying process model to incorporate the required changes is impractical as it requires process expert skills for modeling the process from scratch, requires unacceptably high turnaround times, and is, from a user experience point of view, not sufficiently adjusted to the specific contextual situation and process end user role. In particular, it does not guide an end user in performing the needed changes and also does not reduce the inherent complexity of performing process model changes in a full process modeling environment.